It is known to use call centers to facilitate the receipt, response and routing of incoming telephonic communications relating to customer service and sales. Generally, a customer communicates via telephone with a customer service representative (“CSR”) or contact center agent who is responsible for responding to customer inquiries and/or directing the customer to an appropriate individual, department, information source, or service as required to satisfy the customer's needs.
It is also well known to monitor calls and other electronic communications between a customer and a call center. Accordingly, call centers typically employ individuals responsible for listening to the conversation, or monitoring other types of electronic communications, between a customer and an agent. Many companies have in-house call centers to respond to customer complaints and inquiries. In many cases, however, it has been found to be cost effective for a company to use a third party call center to handle such inquiries. Call centers may be located thousands of miles away from a company's location or a customer. This often results in inconsistent and subjective methods of monitoring, training and evaluating contact center agents. These methods also may vary widely from call center to call center.
For typical call centers, call monitoring may occur in real time. In some instances, call centers may accumulate data for later review. Information gathered by a call center is typically used to provide a corrective response, to monitor agents of a call center and to identify possible training needs. Based on the review and analysis of the incoming data, a monitor can make suggestions or recommendations to improve the quality of the customer interaction.
Accordingly, there is a need in the field of customer relationship management (“CRM”) for an objective tool useful in improving the quality of customer interactions with agents, and ultimately customer relationships. In particular, a need exists for an objective monitoring and analysis tool which provides information about a customer's perception of an interaction with a service. In the past, post-interaction data collection methods have been used to survey callers for feedback. Although such surveys have enjoyed some degree of success, their usefulness is directly tied to a customer's willingness to provide data after an interaction.
Recently, there has arisen an increase in the use of electronic mail, social media data feeds and web data and other electronic customer communication data. Conventional call centers do not account for the collection of this type of customer commentary regarding the quality of products or services. As such, a need has arisen for an objective tool useful for monitoring and analyzing not only telephonic communications, but also electronic data transmissions.
Certain psychological behavioral models have been developed as tools to evaluate and understand how and/or why one person or a group of people interacts with another person or group of people. The Process Communication Model® (“PCM”) developed by Dr. Taibi Kahler is an example of one such behavioral model. Specifically, PCM presupposes that all people fall primarily into one of six basic personality types: Reactor, Workaholic, Persister, Dreamer, Rebel and Promoter. Although each person is one of these six types, all people have parts of all six types within them arranged like a “six-tier configuration.” Each of the six types learns differently, is motivated differently, communicates differently, and has a different sequence of negative behaviors in which they engage when they are in distress. Importantly, each PCM personality type responds positively or negatively to communications that include tones or messages commonly associated with another of the PCM personality types. Thus, an understanding of a communicant's PCM personality type offers guidance as to an appropriate responsive tone or message. There exists a need for a system and method that analyzes the underlying behavioral characteristics of customer and agent communications by automatically applying a psychological behavioral model such as, for example PCM, to collected electronic data.
The embodiments described herein should overcome one or more of the deficiencies of conventional systems and methods.